Description: The old adage 'insurance is sold not bought' has been used to dismiss digital insurance and support the old agent model of distribution. However, modern distribution systems address this with personalization. This is not simply a customized application form based on age or gender. Personalization is much more dynamic and happens in real-time. It's about tailoring the end-to-end experience to meet the needs and expectations of the specific applicant. The core tools to achieve this are AI learning and nudges from behavioral science.

Description: Agility, responsiveness, and real-time access to data are critical today, and they become even more critical tomorrow. As business leaders, we need to drive a more responsive decision-making culture, and we can do this by utilizing the concept of continuous improvement. Discover how an agile company can increase its financial IQ to improve the speed, openness, confidence, and frequency of finance-led decision-making - and ultimately position finance as the strategic core of the organization.

Description: In this session, we will explore the opportunities and challenges of leveraging AI tools to support valuation actuaries in their work. We will begin by introducing the concept of large language models (LLMs), discussing their capabilities, limitations, and potential errors. We will then delve into case studies that demonstrate how LLMs can be effectively utilized to reference actuarial documents. The session will also address key considerations when developing AI tools to mitigate errors, enhance safety and security, and improve overall efficiency. The case studies will cover fine-tuning and information retrieval techniques such as retrieval augmented generation (RAG). Our goal is to provide attendees with a foundational understanding of the nature of LLMs and offer practical insights and ideas for actuaries to build their own processes and tools that ensure accountability, safety, and efficiency.

Description: With the unprecedented proliferation in the size and complexity of data over the past decade, actuaries have invested considerable time and energy in the development of new skills and expertise in order to be able to understand and use “big data” to its fullest potential in the development of actuarial work product.

Description: The actuarial profession is changing rapidly and the skills needed to be successful are also changing. In this session, we will debate key topics and questions, such as: What is the predominant future career path for actuaries? Specialists or generalists? Does the actuarial profession have a meaningful value prop outside our core domains e.g. insurance? What skills are needed for the actuary of the future? What’s the best approach to improve actuarial storytelling to non-actuarial audiences? What’s the role of actuaries to managing and predicting emerging trends and assumptions? What is the role of actuaries in relation to development and ownership of advanced modeling? Is the future actuarial profession smaller/larger than it is today? In either case, how does it differ from today in terms of make-up, deployment, function, purpose, value add, etc.?

Description: One of the most effective ways to convey quantitative results is via data visualization. However, many times actuaries have been ineffective in doing this. In this session, you will see a demonstration of certain dataviz choices that make communicating results more effective in terms of graph type choice, graph element styles, colors and more. All examples will be in Excel-and doesn't require Visual Basic for Applications (VBA)! Nothing too fancy! I want to distribute working files to attendees before the session so they can follow along with how to build the graphs, make changes, etc. Graph choices will include line graph, tile grid map and jitter graph.

Description: Creating a predictive model is one thing, but then taking that model and getting full stakeholder buy-in is another. Learn from presenters' experiences and insights on proving model effectiveness in the long-term care (LTC), life and annuity spaces. Explore various topics such as feasibility, model transparency, fairness and equity, ROI measurement, data assets and compliance, infrastructure and more. By the end of the session, you will gain an understanding of how to navigate the challenges of proving the effectiveness of predictive modeling and obtaining management buy-in.

Description: How do we take a Minimum Viable Products (MVP) approach to launch new insurance products? Join this moderated discussion and focus on three key development aspects: Distribution, Systems, and the design and pricing of the Insurance product itself. Come discuss reasons to choose an MVP approach and how it solves many of the product launch challenges.

Description: Welcome to the future of insurance, for actuaries and non-actuaries! Discover how cutting-edge AI models are revolutionizing underwriting, risk assessment, and customer experience for the insurance industry. Experts in management consulting and actuarial consulting firms will provide valuable insights into the consideration and challenges surrounding the adoption of Generative AI.

Description: As data continues to become more robust and readily available, there has been a push in the actuarial field to transition away from Excel to SQL and Python native cloud-based platforms. While these platforms are widely used and powerful, they present challenges for the actuarial industry: Requiring processes to be production-ready from the onset, technical expertise for integration and robust documentation. Low-code tools provide a unique alternative solution, which works when the organization's operating model allows for actuarial and IT to work together, giving actuaries the flexibility they need while maintaining a level of control followed by the organization In this session, you will watch demonstrations that showcase low-code tools and their use case in the actuarial space. See how these low-barrier-to-entry tools can be leveraged to create robust processes. We will discuss solutions such as Alteryx and Dataiku and how low-code tools can integrate with coding languages such as Python to create more robust processes.